Conventional topographical surface mapping technologies that have been used to create elevation rasters, maps, and images, tend to approximate the surface of the earth relatively coarsely. For example, DTED-2 (Digital Terrain Elevation Data) format can use spatial resolutions (i.e., different cell sizes) of 30×30 meters with a vertical resolution of 1 meter. The data is typically stored as a 16 bit integer raster (−32 km−+32 km), which provides enough range to represent any point on earth, but not a high enough resolution to map many above ground features (i.e., trees, buildings, etc.) due to the large cell sizes. Note the terms raster and image, as well as cell and pixel, are used interchangeably herein.
Contemporary surface mapping systems can provide highly detailed images with cell sizes smaller than one square meter and vertical resolutions below 1 cm. These systems can create images rich in detail and content including buildings, cars, brush, trees, or other surface features given the small cell size and shallow vertical resolution. As a result, these images can result in very large data files that render conventional compression technologies (e.g., LZW) ineffective. In many modern systems, users have the choice between lossless compression (e.g., LZW) on the one hand, which can be ineffective on high detail, highly noisy data, and lossy compression methods (e.g., jpg) on the other hand, which can produce arbitrarily large compression errors for a single pixel. Better compression methods are needed that can be lossy, and provide adequate compression ratios for contemporary high resolution raster files.